Emotion Recognition using Speech Features
Emotion Recognition Using Speech Features covers emotion-specific features present in speech and discussion of suitable models for capturing emotion-specific information for distinguishing different emotions. The content of this book is important for designing and developing natural and sophistica...
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| Glavni autori: | , |
|---|---|
| Format: | Livre numérique |
| Jezik: | Anglais |
| Izdano: |
New York, NY :
Springer New York
2013.
Cham : Springer Nature |
| Serija: | SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning
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| Online pristup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Bilješka: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Emotion Recognition using Speech Features, Texte imprimé, 9781461451440 • Emotion recognition using speech features, Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi, New York, Springer, 2013, 1 vol. (xii, 124 p.), SpringerBriefs in electrical and computer engineering, Springerbriefs in speech technology, 978-1-461-45142-6 |
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| 020 | |a 9781461451433 | ||
| 041 | 0 | |a eng | |
| 082 | |a 621.382 | ||
| 100 | 1 | |a Rao, K. Sreenivasa. | |
| 245 | 1 | 0 | |a Emotion Recognition using Speech Features |c by K. Sreenivasa Rao, Shashidhar G. Koolagudi. |
| 260 | |a New York, NY : |b Springer New York. | ||
| 260 | |a Cham : |b Springer Nature, |c 2013. | ||
| 490 | 0 | |a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning |x 2191-7388 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a Introduction -- Speech Emotion Recognition: A Review -- Emotion Recognition Using Excitation Source Information -- Emotion Recognition Using Vocal Tract Information -- Emotion Recognition Using Prosodic Information -- Summary and Conclusions -- Linear Prediction Analysis of Speech -- MFCC Features -- Gaussian Mixture Model (GMM). | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Emotion Recognition Using Speech Features covers emotion-specific features present in speech and discussion of suitable models for capturing emotion-specific information for distinguishing different emotions. The content of this book is important for designing and developing natural and sophisticated speech systems. Drs. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models. Additionally, the authors provide information about using evidence derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Discussion includes global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information; use of complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance; and proposed multi-stage and hybrid models for improving the emotion recognition performance. | ||
| 700 | 1 | |a Koolagudi, Shashidhar G. |4 aut | |
| 776 | 0 | |t Emotion Recognition using Speech Features |b Texte imprimé |z 9781461451440 | |
| 776 | 0 | |0 181825899 |t Emotion recognition using speech features |f Sreenivasa Rao Krothapalli, Shashidhar G. Koolagudi |c New York |n Springer |d 2013 |p 1 vol. (xii, 124 p.) |s SpringerBriefs in electrical and computer engineering, Springerbriefs in speech technology |z 978-1-461-45142-6 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/978-1-4614-5143-3 |z Accès sur la plateforme de l'éditeur | |
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